Software Architect - Dynamical Simulation & AI (Space Division)

About the Role We are seeking a?Software Architect?to lead the design and development of a next-generation?dynamical simulation engine?that combines?high-performance numerical computation,?control-theoretic modeling, and?AI-driven predictive analytics. You will architect and implement the computational core?designing scalable, precision-focused systems running on?CPU and GPU?and integrate AI/ML modules for learning, estimation, and prediction. This is a hands-on, technically deep role with architectural ownership and cross-team leadership.

Key Responsibilities Core Architecture & Simulation Engine

• Architect and implement a?dynamical system simulation framework?for complex, time-dependent physical and engineered processes.
• Develop and optimize numerical algorithms for?multi-core CPUs and GPUs?using?C/C++,?Python, and?CUDA/OpenCL.
• Integrate?control-theoretic models, including feedback systems, stability analysis, and perturbation analysis.
• Define simulation data structures, solver architectures, and modular interfaces for extensibility.

• Collaborate with AI/ML teams to embed?predictive models?and?data-driven controllers?into the simulation loop.
• Architect efficient data exchange and compute workflows between numerical solvers and AI inference engines.
• Optimize hybrid AI + physics simulation performance.

• Profile and tune performance-critical components for compute efficiency, memory management, and scalability.
• Develop benchmarking tools and regression frameworks for algorithm validation.

• Lead a small team of simulation and algorithm engineers.
• Work closely with the?Application Tech Lead?and UI/backend teams for seamless integration.
• Establish architectural standards, review processes, and documentation practices.

• Bachelor?s or Master?s degree in?Computer Science, Electrical/Mechanical Engineering, Control Systems, Applied Mathematics, or a related field.
• 10+ years?of experience in high-performance computational software development.
• Deep understanding of:
• Control theory, dynamical systems, and feedback mechanisms
• Numerical methods, ODE/PDE solvers, and stability analysis
• Parallel and GPU computing?(CUDA, OpenCL, OpenMP)
• C/C++,?Python, and scientific computing libraries
• Proven experience integrating?AI/ML frameworks?(PyTorch, TensorFlow) with numerical systems.

• Experience building?simulation engines from scratch, not just using existing platforms.
• Familiarity with?distributed compute systems, profiling, and optimization tools.
• Exposure to?DevOps for scientific codebases?(CMake, CI/CD, Docker).

• Strong analytical and problem-solving skills rooted in mathematical reasoning.
• Excellent communication and technical documentation abilities.
• Proven leadership and mentoring capability.

Benefits We offer great career growth, ESOPs, Gratuity, PF and Health Insurance.